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Applying Business Intelligence for Knowledge Generation in Tourism Destinations – A Case Study from Sweden

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Tourism and Leisure

Abstract

The book chapter at hand presents a knowledge infrastructure recently implemented as genuine novelty at the leading Swedish tourism destination, Åre. By applying a Business Intelligence (BI) approach, the Destination Management Information System Åre (DMIS-Åre) drives knowledge creation and application as a precondition for organizational learning at tourism destinations. Schianetz et al.’s (2007) concept of the ‘Learning Tourism Destination’ and the ‘Knowledge Destination Framework’ (Höpken et al. 2011) build the theoretical fundaments for the technical architecture of the presented BI application. After having briefly discussed the set of indicators measuring destination performance and tourist experience, the book chapter highlights how DMIS-Åre is used to gain new knowledge from customer-based destination processes, like ‘Web- Navigation’, ‘Booking’ and ‘Feedback’. The chapter ends by outlining future research, such as the application of real-time Business Intelligence for gaining knowledge on tourists’ on-site behavior at the destination in real-time.

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References

  • Back, A., Enkel, E. & V. Krogh, G. (2007). Knowledge Networks for Business, New York: Springer.

    Google Scholar 

  • Bloom, J. (2004). Tourist Market Segmentation with Non-Linear Techniques. Tourism Management, 25(6): 723–733.

    Article  Google Scholar 

  • Bornhorst, T., Ritchie, J.R. & Sheehan, L. (2010). Determinants for DMO & Destination Success: An Empirical Examination, Tourism Management, 31: 572–589.

    Article  Google Scholar 

  • Buhalis, D. (2006). The Impact of ICT on Tourism Competition, In A. Paptheodorou (ed.), Corporate Rivalry and Market Power, London: IB Tauris: 143–171.

    Google Scholar 

  • Chekalina, T., Fuchs, M. & Lexhagen, M. (2014). A-Value Creation Perspective on the Customer-based Brand Equity Model for Tourism Destinations, Finnish Journal of Tourism Research, (in print).

    Google Scholar 

  • Chekalina, T., Fuchs, M. & Lexhagen, M. (2013). Determinants of the Co- Created Destination Experience, In: Kozak, M., Andreu, L.; Gnoth, J., Lebe S. & Fyall, A. (eds.), Tourism Marketing: On Both Sides of the Counter, Cambridge Publishing, 57–79.

    Google Scholar 

  • Coles, T., Hall, M. & Duval, D. (2006). Tourism: A Post-Disciplinary Enquiry, Current Issues in Tourism, 9(1): 4–5.

    Article  Google Scholar 

  • Dwyer, L. & Kim, C. (2003). Destination Competitiveness: Determinants and Indicators. Current Issues in Tourism Research, 6(5): 369–417.

    Article  Google Scholar 

  • Fuchs, M. & Weiermair, K. (2004). Destination Benchmarking - An Indicator System’s Potential for Exploring Guest Satisfaction. Journal of Travel Research, 42(3): 212–225.

    Article  Google Scholar 

  • Fuchs, M. & Höpken, W. (2009). Data Mining in Tourism (In German: ‚Data Mining im Tourismus‘), Praxis der Wirtschaftsinformatik, 270(12): 73–81.

    Article  Google Scholar 

  • Fuchs, M., Höpken, W., Föger, A. & Kunz, M. (2010a). E-Business Readiness, Intensity, and Impact – An Austrian DMO Study, Journal of Travel Research, 49(2): 165–178.

    Article  Google Scholar 

  • Fuchs, M., Scholochow, Ch., & Höpken, W. (2010b). E-Business Adoption, Use and Value Creation – An Austrian Hotel Study, Information Technology and Tourism, 11 (4): 267–284.

    Article  Google Scholar 

  • Fuchs, M., Eybl, A. & Höpken, W. (2011). Successfully Selling Accommodation Packages at Online Auctions – The Case of eBay Austria, Tourism Management, 32(5): 1166–1175.

    Article  Google Scholar 

  • Fuchs, M. & Zanker, M. (2012). Multi-criteria Ratings for Recommender Systems: An Empirical Analysis in the Tourism Domain, In: Huemer, C. & Lop, P (eds.) E-Commerce and Web Technologies, Lecture Notes in Business Information Processing, Springer, Heidelberg, London, 123(3): 100–111.

    Google Scholar 

  • Fuchs, M., Abadzhiev, A., Svensson, B, Höpken, W. & Lexhagen, M. (2013). A Knowledge Destination Framework for Tourism Sustainability – a Business Intelligence Application from Sweden, Tourism - An Interdisciplinary Journal, 61(2): 121–148.

    Google Scholar 

  • Gräbner, D., Zanker, M., Fliedl, G. & Fuchs, M. (2012). Classification of Customer Reviews based on Sentiment Analysis – The Case of TripAdvisor. In: Fuchs, M., Ricci, F. & Cantoni, L. (eds.), Information and Communication Technologies in Tourism, Springer, New York: 460–470.

    Google Scholar 

  • Gravic (2013). Shadowbase for Real-Time BI, www.gravic.com/shadowbase/ (retrieved March 2013).

  • Gretzel, U. & Fesenmaier, D.R. (2004). Implementing a Knowledge-based Tourism Marketing Information System, Journal of Information Technology & Tourism, 6(2): 245–255.

    Google Scholar 

  • Höpken, W., Fuchs, M. & Zanker, M. (2005). etPlanner - A Hybrid Recommender System for Mobile Travel Planning. The Austrian Society for Artificial Intelligence, 24(2): 26–31.

    Google Scholar 

  • Höpken, W., Fuchs, M., Zanker, M. & Beer, Th. (2010). Context-based Adaptation of Mobile Applications in Tourism, Information Technology and Tourism, 12(2): 175–195.

    Article  Google Scholar 

  • Höpken, W., Fuchs, M., Keil, D. & Lexhagen, M. (2011). The Knowledge Destination – A Customer Information-based Destination Management Information System, In: R. Law, M. Fuchs & F. Ricci (Eds.), Information and Communication Technologies in Tourism, New York: Springer: 417–429.

    Google Scholar 

  • Höpken, W., Deubele, Ph, Höll, G., Kuppe, J., Schorpp, D., Licones, R. & Fuchs, M. (2012). Digitalizing Loyalty Cards in Tourism, In: Fuchs, M., Ricci, F. & Cantoni, L. (eds.), Information and Communication Technologies in Tourism, Springer, New York: 272–283.

    Google Scholar 

  • Höpken, W., Fuchs, M., Höll, G., Keil, D. & Lexhagen, M. (2013). Multidimensional Data Modeling for a Destination Data Warehouse, In: Cantoni, L. & Xiang, Ph. (eds.) Information and Communication Technologies in Tourism 2013, Springer, New York: 157–169.

    Chapter  Google Scholar 

  • Höpken, W., Fuchs, M. & Lexhagen, M. (2014). The Knowledge Destination – Applying Methods of Business Intelligence to Tourism. In Wang, J. (ed.) Encyclopedia of Business Analytics and Optimization, Pennsylvania, IGI Global: 307–321.

    Google Scholar 

  • Jafari, J. (2001). The Scientification of Tourism. In: V. Smith, & M. Brent (Eds.), Hosts and Guests Revisited: Tourism Issues of the 21st Century. New York: Cognizant: 28–41.

    Google Scholar 

  • Jannach, D., Zanker, M. & Fuchs, M. (2013). Multi-criteria Customer-Feedback for Improved Recommender Systems in Tourism. Journal of Information Technology and Tourism, (in print).

    Google Scholar 

  • Kimball, R., Ross, M., Thronthwaite, W., Mundy, J. & Becker, B. (2008). The Data Warehouse Lifecycle Toolkit, 2nd Edition, Indianapolis: Wiley & Sons.

    Google Scholar 

  • Larose, D.T. (2005). Discovering Knowledge in Data. New Jersey: John Wiley & Sons.

    Google Scholar 

  • Magnini, V., Honeycutt, E., & Hodge, S. (2003). Data Mining for Hotel Firms: Use and Limitations, Cornell Hotel and Restaurant Administration Quarterly, 44(Dec): 94–105.

    Article  Google Scholar 

  • Min, H., Min., H. & Emam, A (2002). A Data Mining Approach to develop the Profile of Hotel Customers. International Journal of Contemporary Hospitality Management, 14(6): 274–285.

    Article  Google Scholar 

  • Palmer, A., Montano, J.J. & Sesé A. (2006). Designing an Artificial Neural Network for Forecasting Tourism Time Series. Tourism Management, 27(4): 781–790.

    Article  Google Scholar 

  • Pitman, A., Zanker, M., Fuchs, M. & Lexhagen, M. (2010). Web Usage Mining in Tourism. In: U. Gretzel, R. Law, & M. Fuchs (Eds.), Information and Communication Technologies in Tourism, New York: Springer: 393–403.

    Google Scholar 

  • Pyo, S., Uysal, m. & Chang, H. (2002). Knowledge Discovery in Databases for Tourist Destinations. Journal of Travel Research, 40(4): 396–403.

    Article  Google Scholar 

  • Pyo, S. (2005). Knowledge Map for Tourist Destinations, Tourism Management, 26(4): 583–594.

    Article  Google Scholar 

  • Rasinger, J., Fuchs, M., Höpken, W. & Beer, Th. (2009). Building a Mobile Tourist Guide based on Tourists’ On-Site Information Needs. Tourism Analysis, 14(4): 483–502.

    Article  Google Scholar 

  • Ritchie, R.J.B. & Ritchie J.R.B. (2002). A Framework for an Industry supported Destination Marketing Information System. Tourism Management, 23(2): 439–454.

    Article  Google Scholar 

  • Shaw, G. & Williams, A. (2009). Knowledge Transfer and Management in Tourism Organisations. Tourism Management, 30(3): 325–335.

    Article  Google Scholar 

  • Schianetz, K., Kavanagh, L. & Lockington, D. (2007). The Learning Tourism Destination, Tourism Management, 28(3): 1485–1496.

    Article  Google Scholar 

  • Schmunk, S., Höpken, W., Fuchs, M. & Lexhagen, M. (2014). Sentiment Analysis – Implementation and Evaluation of Methods for Sentiment Analysis with Rapid-Miner®, In Xiang, Ph. & Tussyadiah, I. (eds.) Information and Communication Technologies in Tourism, Springer, New York: 253–265.

    Google Scholar 

  • Sidali, K. L., Fuchs, M. & Spiller, A. (2012). The Effect of Electronic Reviews on Consumer Behavior – An Explorative Study, In: Sigala, M., Gretzel, U. & Vangelis, R. (eds.), Web 2.0 in Travel, Tourism and Hospitality: Theory, Practices and Cases, Ashgate Publishing, Surrey, 239–253.

    Google Scholar 

  • Wang, Y. & Russo, S.M. (2007). Conceptualizing and Evaluating the Functions of Destination Marketing Systems, Journal of Vacation Marketing, 13(3): 187–203.

    Article  Google Scholar 

  • Wong J., Chen H., Chung, P., & Kao, N. (2006). Identifying Valuable Travelers and their next Foreign Destination by applying Data Mining Techniques; Asia Pacific Journal of Tourism Research, 11(4): 355–373.

    Article  Google Scholar 

  • Zanker, M, Jessenitschnig, M. & Fuchs, M. (2010). Automated Semantic Annotation of Tourism Resources based on Geo-Spatial Data, Information Technology and Tourism, 11(4): 341–354.

    Article  Google Scholar 

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Correspondence to Matthias Fuchs .

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Fuchs, M., Höpken, W., Lexhagen, M. (2015). Applying Business Intelligence for Knowledge Generation in Tourism Destinations – A Case Study from Sweden. In: Pechlaner, H., Smeral, E. (eds) Tourism and Leisure. Springer Gabler, Wiesbaden. https://doi.org/10.1007/978-3-658-06660-4_11

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  • DOI: https://doi.org/10.1007/978-3-658-06660-4_11

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  • Publisher Name: Springer Gabler, Wiesbaden

  • Print ISBN: 978-3-658-06659-8

  • Online ISBN: 978-3-658-06660-4

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